Alle Papers – Machine Learning im Gesundheitswesen

Feasibility analysis of conducting observational studies with the electronic health record

A Survey of Deep Learning for Electronic Health Records

Bridging the Gap: Exploring Interpretability in Deep Learning Models for Brain Tumor Detection and Diagnosis from MRI Images

Simulation-derived best practices for clustering clinical data

Diabetes Mellitus Disease Prediction Using Machine Learning Classifiers with Oversampling and Feature Augmentation

Localization of mixed intracranial hemorrhages by using a ghost convolution-based YOLO network

Real-Time Automated Sampling of Electronic Medical Records Predicts Hospital Mortality

Medical Information Mart for Intensive Care: A Foundation for the Fusion of Artificial Intelligence and Real-World Data

Impact of multimorbidity and complex multimorbidity on mortality among older Australians aged 45 years and over: a large population-based record linkage study

The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer’s disease

Intelligent Tutoring Systems

Why these Explanations? Selecting Intelligibility Types for Explanation Goals.

An Effective Approach for Detecting Diabetes using Deep Learning Techniques based on Convolutional LSTM Networks

A gut aging clock using microbiome multi-view profiles is associated with health and frail risk

A physiological and behavioral feature authentication scheme for medical cloud based on fuzzy-rough core vector machine

Subphenotyping depression using machine learning and electronic health records

An interpretable stacking ensemble learning framework based on multi-dimensional data for real-time prediction of drug concentration: The example of olanzapine

Use of Generative AI to Identify Helmet Status Among Patients With Micromobility-Related Injuries From Unstructured Clinical Notes

CardioNet: a manually curated database for artificial intelligence-based research on cardiovascular diseases

Limitations of Deep Learning Attention Mechanisms in Clinical Research: Empirical Case Study Based on the Korean Diabetic Disease Setting

Detecting late-life depression in Alzheimer's disease through analysis of speech and language

Unsupervised anomaly detection of implausible electronic health records: a real-world evaluation in cancer registries

A Deep Learning Model for Estimation of Patients with Undiagnosed Diabetes

Distributed learning of deep neural network over multiple agents